​​Emerging viruses can cause new diseases in humans and animals and proper epidemiological surveillance is essential to detect and characterize such viruses. Given the enormous impact of the COVID-19 pandemics, this course will cover the assembly of the SARS-CoV-2 genome from human patients, characterization of viral variants, and identification of variants of concern (VOCs). The course will also present some innovative methods that can improve the detection of evolutionarily remote viruses. Among other methods, the course will cover the construction of profile HMMs and their application to screening metagenomic datasets for both known and novel viruses.

Virtual machines:

• All students will receive an account in a virtual machine (VM) 
• The VMs will be running Linux and all programs used throughout the course will be available to students
• Access to the VMs will be granted throughout the entire duration of the course. 
• No programs are needed on the local computer, except Zoom

Who is this course for?

This course is intended for graduate students, postdocs and young researchers working in the fields of metagenomics and viral discovery in the CABANA grand challenge areas of communicable diseases, protection of biodiversity, and/or sustainable crop production. 

Applicants must be employed within Latin America only. Additional we cannot accept applications from Chile or Uruguay due to funding restrictions.

Prerequisites

Please note this course will be taught in English, however the trainers are fluent in either Spanish/Portuguese, and can offer language support where feasible. Priority will also be given to those who have not attended a CABANA event yet.

Students should be familiar with using the Linux command line. As the course will be held remotely, all students must have Zoom previously installed on their computers. Also, as classes will be held synchronously, a good Internet connection is mandatory.

A knowledge of virology, especially from previous research experience, is also desirable.

Scientists from underrepresented ethnic and gender groups are especially encouraged to apply for this workshop, for example women and those with Black and/or Indigenous heritage.

What will I learn?

Learning outcomes

After this course you should be able to:  

• Perform SARS-CoV-2 genome assemblies.
• Run and interpret phylogenetic analyses using viral sequence data. 
• Detect Variants of Concern.
• Identify recombination events in SARS-CoV-2.
• Design and apply profile HMMs for viral detection, classification and discovery.

Course content

During this course you will learn about: 

• SARS-CoV-2: Pangolin and GISAID repositories, IQ-TREE, PhyML, Beast, RDP, and Simplot.
• Viral discovery: TABAJARA (profile HMM construction), HMM-Prospector (metagenomic data screening), GenSeed-HMM (seed-driven progressive assembly) and e-Finder (multigene element finder).
• EMBL-EBI resources including COVID-19 Data Portal and MGnify.

Trainers

In order to be considered for a place on this course applicants must complete the online application form.

Incomplete applications will NOT be considered. 

If you have any general queries about the workshop application/registration process please email Guilherme Oliveira and Piv Gopalasingam.

For specific workshop enquiries please email Arthur Gruber 

Please note that this course is free, but unexplained absence will result in blacklisting for future courses and opportunities.

The course will have a maximum of 25 participants and the application will run from October 1st to 31st, 2021. Registration will be dependent on selection upon successful completion of the application process by order of arrival.

Application/Registration will close on 31 October 2021 at 12:00 (GMT)

A bibliography for this course is available to view below. Articles can be accessed here.

Part 1 - Viral discovery 

Alves JM, de Oliveira AL, Sandberg TO, Moreno-Gallego JL, de Toledo MA, de Moura EM, Oliveira LS, Durham AM, Mehnert DU, Zanotto PM, Reyes A, Gruber A. GenSeed-HMM: A Tool for Progressive Assembly Using Profile HMMs as Seeds and its Application in Alpavirinae Viral Discovery from Metagenomic Data. Front Microbiol. 2016 Mar 4;7:269. doi: 10.3389/fmicb.2016.00269. PMID: 26973638; PMCID: PMC4777721.

Cobbin JC, Charon J, Harvey E, Holmes EC, Mahar JE. Current challenges to virus discovery by meta-transcriptomics. Curr Opin Virol. 2021 Sep 27;51:48-55. doi: 10.1016/j.coviro.2021.09.007. Epub ahead of print. PMID: 34592710.

Eddy SR. Profile hidden Markov models. Bioinformatics. 1998;14(9):755-63. doi: 10.1093/bioinformatics/14.9.755. PMID: 9918945.

Eddy SR. Accelerated Profile HMM Searches. PLoS Comput Biol. 2011 Oct;7(10):e1002195. doi: 10.1371/journal.pcbi.1002195. Epub 2011 Oct 20. PMID: 22039361; PMCID: PMC3197634.

Fonseca P, Ferreira F, da Silva F, Oliveira LS, Marques JT, Goes-Neto A, Aguiar E, Gruber A. Characterization of a Novel Mitovirus of the Sand Fly Lutzomyia longipalpis Using Genomic and Virus-Host Interaction Signatures. Viruses. 2020 Dec 23;13(1):9. doi: 10.3390/v13010009. PMID: 33374584; PMCID: PMC7822452.

Oliveira LS, Gruber A. Rational Design of Profile Hidden Markov Models for Viral Classification and Discovery. In: Helder I. N, editor. Bioinformatics [Internet]. Brisbane (AU): Exon Publications; 2021 Mar 20. Chapter 9. PMID: 33877768.

Reyes, A, Alves JM, Durham AM, Gruber A. (2017). Use of profile hidden Markov models in viral discovery: current insights. Advances in Genomics and Genetics 7:29-45. https://doi.org/10.2147/AGG.S136574

Part 2 - SARS-CoV-2 

Dezordi FP, Campos TL, Jeronimo PMC, Aksenen CF, Almeida SP, Wallau GL. ViralFlow: an automated workflow for SARS-CoV-2 genome assembly, lineage assignment, mutations and intrahost variants detection. medRxiv 2021.10.01.21264424; doi: https://doi.org/10.1101/2021.10.01.21264424

Kalyaanamoorthy S, Minh BQ, Wong TKF, von Haeseler A, Jermiin LS. ModelFinder: fast model selection for accurate phylogenetic estimates. Nat Methods. 2017 Jun;14(6):587-589. doi: 10.1038/nmeth.4285. Epub 2017 May 8. PMID: 28481363; PMCID: PMC5453245.

Naveca FG et al. COVID-19 in Amazonas, Brazil, was driven by the persistence of endemic lineages and P.1 emergence. Nat Med. 2021 Jul;27(7):1230-1238. doi: 10.1038/s41591-021-01378-7. Epub 2021 May 25. PMID: 34035535.

Resende PC et al. A Potential SARS-CoV-2 Variant of Interest (VOI) Harboring Mutation E484K in the Spike Protein Was Identified within Lineage B.1.1.33 Circulating in Brazil. Viruses. 2021 Apr 21;13(5):724. doi: 10.3390/v13050724. PMID: 33919314; PMCID: PMC8143327.

Resende PC et al. The ongoing evolution of variants of concern and interest of SARS-CoV-2 in Brazil revealed by convergent indels in the amino (N)-terminal domain of the spike protein. Virus Evol. 2021 Aug 14;7(2):veab069. doi: 10.1093/ve/veab069. PMID: 34532067; PMCID: PMC8438916.

Suchard MA, Lemey P, Baele G, Ayres DL, Drummond AJ, Rambaut A. Bayesian phylogenetic and phylodynamic data integration using BEAST 1.10. Virus Evol. 2018 Jun 8;4(1):vey016. doi: 10.1093/ve/vey016. PMID: 29942656; PMCID: PMC6007674.